MicroRNA Signatures in Neurological Disorders
Bibliographic record
Abstract
A class of small, non-coding transcripts called microRNAs (miRNAs) that play a major role in post-transcriptional gene regulation has recently emerged and become the focus of intense research. MicroRNAs are abundant in the nervous system, where they have key roles in development and are likely to be important mediators of plasticity. A highly conserved pathway of miRNA biogenesis is closely linked to the transport and translatability of mRNAs in neurons. MicroRNAs have been shown to modulate programmed cell death during development. Although there are nearly 750 known human miRNA sequences, each of only approximately 20-25 nucleotides in length that bind to multiple mRNA targets, the accurate prediction of miRNA targets seems to lie just beyond our grasp. Nevertheless, the identification of such targets promises to provide new insights into many facets of neuronal function. In this review, we briefly describe miRNA biogenesis and the principle approaches for studying the function of miRNAs and potential application of miRNAs as biomarkers, diagnostic targets, and potential therapeutic tools of human diseases in general and neurological disorders in particular.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.007 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.004 | 0.000 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; both teacher heads agree on what is shown here.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".